Short- and long-term exposure to air pollution and lack of sunlight are associated with an increased risk of depression: A nested case-control study using meteorological data and national sample cohort data

Long-term effects of fine particulate matter components on depression among middle-aged and elderly adults in China: A nationwide cohort study

BACKGROUND

Fine particulate matter (PM2.5) has been implicated in various health concerns. However, a comprehensive understanding of the specific PM2.5 components affecting depression remains limited.

METHODS

This study conducted a Cox proportional-hazards model to assess the effect of PM2.5 components on the incidence of depression based on the China Health and Retirement Longitudinal Study (CHARLS). Participants with 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) score of 10 or higher were classified as exhibiting depression.

RESULTS

Our findings demonstrated a significant positive correlation between long-term exposure to black carbon (BC), sulfate (SO42-), and organic matter (OM) components of PM2.5 and the prevalence of depression. Per 1 Interquartile Range (IQR) increment in 3-year average concentrations of BC, OM, and SO42- were associated with the hazard ratio (HR) of 1.54 (95 % confidence intervals (CI): 1.44, 1.64), 1.24 (95%CI: 1.16, 1.34) and 1.25 (95%CI: 1.16, 1.35). Notably, females, younger individuals, those with lower educational levels, urban residents, individuals who were single, widowed, or divorced, and those living in multi-story houses exhibited heightened vulnerability to the adverse effects of PM2.5 components on depression.

LIMITATIONS

Firstly, pollutant data is confined to subjects' fixed addresses, overlooking travel and international residence history. Secondly, the analysis only incorporates five fine particulate components, leaving room for further investigation into the remaining fine particulate components in future studies.

CONCLUSIONS

This study provides robust evidence supporting the detrimental impact of PM2.5 components on depression. The identification of specific vulnerable populations contributes to a deeper understanding of the underlying mechanisms involved in the relationship between PM2.5 components and depression.

Long-term Exposure to Ambient Air Pollution and its Association with Mental Well-Being, Depression and Anxiety: A Nationally Representative Study

INTRODUCTION

Exposure to ambient air pollution may play a role in the onset of common mental disorders like depressive and anxiety disorders. The association of long-term exposure to particles smaller than 10 μm (PM10) with these diseases remains unclear. This study aimed to estimate the association of long-term exposure to PM10 with mental well-being and the frequency of probable diagnosis of common mental disorders.

METHODS

A nationally representative cross-sectional study was done in mainland Portugal. Long-term exposure was estimated through one-year average concentrations of PM10, calculated with data from the Portuguese Environment Agency, attributed individually considering individuals' postal codes of residence. The mental well-being and the probable diagnosis of common mental disorders were ascertained through the five-item Mental Health Inventory scale. Linear and Robust Poisson regression models were computed to estimate change percentages, prevalence ratios (PR), and their 95% confidence intervals (95% CI).

RESULTS

The median (interquartile range) concentration of PM10 was 18.6 (15.3 - 19.3) μg/m3. The mental well-being score was 72 (56 - 84) points, on a scale from 0 to 100. A probable diagnosis of common mental disorders was found in 22.7% (95% CI: 20.0 to 25.6). Long-term exposure to PM10 was associated with a non-statistically significant decrease in the mental well-being score [for each 10 μg/m³ increment in one-year average PM10 concentrations, there was a 2% (95% CI: -8 to 4) decrease], and with a non-statistically significant increase in the common mental health frequency (PR = 1.012, 95% CI: 0.979 to 1.045).

CONCLUSION

We did not find statistically significant associations between long-term exposure to PM10 and mental well-being or the frequency of probable diagnosis of common mental disorders. These results may be explained by the reduced variability in the exposure values, given the geographical distribution and functioning of the network of air quality monitoring stations. This study contributes with evidence for low levels of air pollutants, being one of the first to adjust for individual and aggregate-level variables. Moreover, to the best of our knowledge, this was the first nationally representative, population-based study conducted on the Portuguese population using real-life data. Maintaining a robust and nationwide air quality monitoring network is essential for obtaining quality exposure data.

Association between short- and medium-term exposure to air pollutants and depressive episode using comprehensive air quality index among the population in South Korea

BACKGROUND

Currently, air pollution is suggested as a risk factor for depressive episodes. Our study aimed to consider multiple air pollutants simultaneously, and continuously evaluate air pollutants using comprehensive air quality index (CAI) with depressive episode risk.

METHODS

Using a nationally representative sample survey from South Korea between 2014 and 2020, 20,796 participants who underwent health examination and Patient Depression Questionnaire-9 were included in the study. Six air pollutants (PM10, PM2.5, O3, CO, SO2, NO2) were measured for the analysis. Every air pollutant was standardized by air quality index (AQI) and CAI was calculated for universal representation. Using logistic regression, short- and medium-term exposure by AQI and CAI with the risk of depressive episode was calculated by odds ratio and 95 % confidence interval (CI). Furthermore, consecutive measurements of CAI over 1-month time intervals were evaluated with the risk of depressive episodes. Every analysis was conducted seasonally.

RESULTS

There were 950 depressive episodes occurred during the survey. An increase in AQI for short-term exposure (0-30 days) showed higher risk of depressive episode in CO, while medium-term exposure (0-120 days) showed higher risk of depressive episode in CO, SO2, PM2.5, and PM10. During the cold season, the exposure to at least one abnormal CAI within 1-month intervals over 120 days was associated with a 68 % (95 % CI 1.11-2.54) increase in the risk of depressive episode.

CONCLUSIONS

Short- and medium-term exposure of air pollution may be associated with an increased risk of depressive episodes, especially for cold season.

Effects of short- and long-term exposures to multiple air pollutants on depression among the labor force: A nationwide longitudinal study in China

BACKGROUND

Depression prevalence has surged within the labor force population in recent years. While links between air pollutants and depression were explored, there was a notable scarcity of research focusing on the workforce.

METHODS

This nationwide longitudinal study analyzed 27,457 workers aged 15-64. We estimated monthly mean concentrations of fine particulate matter (PM2.5), its primary components, and Ozone (O3) at participants' residences using spatiotemporal models. To assess the relationship between short- (1 to 3 months) and long-term (1 to 2 years) exposure to various air pollutants and depressive levels and occurrences, we employed linear mixed-effects models and mixed-effects logistic regression. We considered potential occupational moderators, such as labor contracts, overtime compensation, and total annual income.

RESULTS

We found significant increases in depression risks within the workforce linked to both short- and long-term air pollution exposure. A 10 μg/m3 rise in 2-year average PM2.5, black carbon (BC), and O3 concentrations correlated with increments in depressive scores of 0.009, 0.173, and 0.010, and a higher likelihood of depression prevalence by 0.5 %, 12.6 %, and 0.7 %. The impacts of air pollutants and depression were more prominent in people without labor contracts, overtime compensation, and lower total incomes.

CONCLUSION

Exposures to air pollutants could increase the risk of depression in the labor force population. The mitigating effects of higher income, benefits, and job security against depression underscore the need for focused mental health interventions.

Association between solar radiation and mood disorders among Gulf Coast residents

BACKGROUND

Climate factors such as solar radiation could contribute to mood disorders, but evidence of associations between exposure to solar radiation and mood disorders is mixed and varies by region.

OBJECTIVE

To evaluate the association of solar radiation with depression and distress among residents living in U.S. Gulf states.

METHODS

We enrolled home-visit participants in the Gulf Long-Term Follow-up Study who completed validated screening questionnaires for depression (Patient Health Questionnaire-9, N = 10,217) and distress (Kessler Psychological Distress Questionnaire, N = 8,765) for the previous 2 weeks. Solar radiation estimates from the Daymet database (1-km grid) were linked to residential addresses. Average solar radiation exposures in the seven (SRAD7), 14 (SRAD14), and 30 days (SRAD30) before the home visit were calculated and categorized into quartiles (Q1-Q4). We used generalized linear mixed models to estimate prevalence ratios (PR) and 95% confidence intervals (CI) for associations between solar radiation and depression/distress.

RESULTS

Higher levels of SRAD7 were non-monotonically inversely associated with depression [PRVs.Q1 (95%CI): Q2 = 0.81 (0.68, 0.97), Q3 = 0.80 (0.65, 0.99), Q4 = 0.88 (0.69, 1.15)] and distress [PRVs.Q1 (95%CI): Q2 = 0.76 (0.58, 0.99), Q3 = 0.77 (0.57, 1.06), Q4 = 0.84 (0.58, 1.22)]. Elevated SRAD14 and SRAD30 appeared to be associated with decreasing PRs of distress. For example, for SRAD14, PRs were 0.86 (0.63-1.19), 0.80 (0.55-1.18), and 0.75 (0.48-1.17) for Q2-4 versus Q1. Associations with SRAD7 varied somewhat, though not significantly, by season with increasing PRs of distress in spring and summer and decreasing PRs of depression and distress in fall.

IMPACT STATEMENT

Previous research suffered from exposure misclassification, which impacts the validity of their conclusions. By leveraging high-resolution datasets and Gulf Long-term Follow-up Cohort, our findings support an association between increased solar radiation and fewer symptoms of mood disorders.

Association of Residential Greenness Exposure with Depression Incidence in Adults 50 Years of Age and Older: Findings from the Cohort Study on Global AGEing and Adult Health (SAGE) in China

BACKGROUND

Depression is a social and public health problem of great concern globally. Identifying and managing the factors influencing depression are crucial for preventing and decreasing the burden of depression.

OBJECTIVES

Our objectives are to explore the association between residential greenness and the incidence of depression in an older Chinese population and to calculate the disease burden of depression prevented by greenness exposure.

METHODS

This study was the Chinese part of the World Health Organization Study on Global AGEing and Adult Health (WHO SAGE). We collected the data of 8,481 residents ≥ 50 years of age in China for the period 2007-2018. Average follow-up duration was 7.00 (± 2.51 ) years. Each participant was matched to the yearly maximum normalized difference vegetation index (NDVI) at their residential address. Incidence of depression was assessed using the Composite International Diagnostic Interview (CIDI), self-reports of depression, and/or taking depression medication. Association between greenness and depression was examined using the time-dependent Cox regression model with stratified analysis by sex, age, urbanicity, annual family income, region, smoking, drinking, and household cooking fuels. Furthermore, the prevented fraction (PF) and attributable number (AN) of depression prevented by exposure to greenness were estimated.

RESULTS

Residential greenness was negatively associated with depression. Each interquartile range (IQR) increase in NDVI 500 -m buffer was associated with a 40% decrease [hazard ratio  ( HR ) = 0.60 ; 95% confidence interval (CI): 0.37, 0.97] in the risk of depression incidence among the total participants. Subgroup analyses showed negative associations in urban residents (HR = 0.32 ; 95% CI: 0.12, 0.86) vs. rural residents, in high-income residents (HR = 0.28 ; 95% CI: 0.11, 0.71) vs. low-income residents, and in southern China (HR = 0.50 ; 95% CI: 0.26, 0.95) vs. northern China. Over 8.0% (PF = 8.69 % ; 95% CI: 1.38%, 15.40%) and 1,955,199 (95% CI: 310,492; 3,464,909) new cases of depression may be avoided by increasing greenness exposures annually across China.

DISCUSSION

The findings suggest protective effects of residential greenness exposure on depression incidence in the older population, particularly among urban residents, high-income residents, and participants living in southern China. The construction of residential greenness should be included in community planning. https://doi.org/10.1289/EHP13947.

Relationship between Environmental Conditions and Utilisation of Community-Based Mental Health Care: A Comparative Study before and during the COVID-19 Pandemic in Italy

(1) Background: Lower socioeconomic status increases psychiatric service use, exacerbated during the COVID-19 pandemic by environmental stressors like air pollution and limited green spaces. This study aims to assess the influence of sociodemographic and environmental factors on mental health service utilisation. (2) Methods: This retrospective study uses an administrative database focusing on community mental health services in Northeast Italy. Spatial and temporal analyses were used to address space-time dependencies. (3) Results: Findings showed that sociodemographic factors like living in rented apartments and lower education levels predicted higher mental health service use. Environmental factors, such as elevated NO2 levels and, before the pandemic, lower solar radiation and tree cover, correlated with increased service utilisation. COVID-19 reduced most of the pre-existing differences associated with these factors across census blocks with a different composition of sociodemographic and environmental factors. (4) Conclusions: These findings contribute to a better understanding of the impact of the environment on public mental health.

The impact of sunlight exposure on brain structural markers in the UK Biobank

Sunlight is closely intertwined with daily life. It remains unclear whether there are associations between sunlight exposure and brain structural markers. General linear regression analysis was used to compare the differences in brain structural markers among different sunlight exposure time groups. Stratification analyses were performed based on sex, age, and diseases (hypertension, stroke, diabetes). Restricted cubic spline was performed to examine the dose-response relationship between natural sunlight exposure and brain structural markers, with further stratification by season. A negative association of sunlight exposure time with brain structural markers was found in the upper tertile compared to the lower tertile. Prolonged natural sunlight exposure was associated with the volumes of total brain (β: - 0.051, P < 0.001), white matter (β: - 0.031, P = 0.023), gray matter (β: - 0.067, P < 0.001), and white matter hyperintensities (β: 0.059, P < 0.001). These associations were more pronounced in males and individuals under the age of 60. The results of the restricted cubic spline analysis showed a nonlinear relationship between sunlight exposure and brain structural markers, with the direction changing around 2 h of sunlight exposure. This study demonstrates that prolonged exposure to natural sunlight is associated with brain structural markers change.

Reliability and validity of the Chinese version of the sunlight exposure questionnaire

Objective

This study aimed to translate and validate the reliability and validity of the Chinese version of the Philippines Sunlight Exposure Questionnaire.

Methods

A total of 392 Chinese individuals aged at least 18 years, residing in various cities in Sichuan province for at least 1 year, were recruited. The reliability of the Chinese version of the questionnaire was measured through internal consistency, split-half reliability, and retest reliability, while validity was determined using the content validity index and the structure validity index.

Results

The Chinese version of the Sunlight Exposure Questionnaire, which includes 19 items covering 5 factors, demonstrated McDonald's omega coefficient of 0.788. The split-half reliability of the questionnaire was 0.823, and the retest reliability was 0.940. The content validity index (S-CVI) was 0.952. The five-factor structure, supported by eigenvalues, explained 66.2% of the total variance. Confirmatory factor analysis indicated favorable model fit.

Results

The chi-square value degrees of freedom ratio (χ2/df) = 1.852, the goodness-of-fit index (GFI) = 0.938, the normed fit index (NFI) = 0.922, the incremental fit index (IFI) = 0.962, the comparative fit index (CFI) = 0.962, the Tucker-Lewis index (TLI) = 0.952, and root mean square error of approximation (RMSEA) = 0.047. The indicators of the fit of the model were within reasonable bounds.

Conclusion

The Chinese version of the Sunlight Exposure Questionnaire shows validity and good reliability for assessing sun exposure among adults in a Chinese cultural context.

The short-term effect of ambient particulate matter on suicide death

BACKGROUND

Air pollution can cause various respiratory and neurological diseases and continuous exposure can lead to death. Previous studies have reported that particulate matter (PM) exposure increases the risk of depression, suicidal thoughts, and suicidal death; however, the results are inconsistent and limited. This study aimed to examine the relationship between short-term PM exposure and suicide deaths, as well as investigate the short-term effects of PM on suicide death within vulnerable groups based on factors such as sex, age group, suicide-related information (note, method, and cause), psychiatric disorders, and physical diseases.

METHODS

Data on a total of 28,670 suicide deaths from 2013 to 2017, provided by the Korea Foundation for Suicide Prevention, were analyzed. The study design employed a time-series analysis with a two-stage approach. In the first step, a generalized additive model combined with a distributed lag nonlinear model was used to estimate the short-term effect of PM exposure on suicide risk specific to each city. In the second step, the estimated results from each city were pooled through a meta-analysis to derive the overall effect. We determined the effects of single lag, cumulative lag, and moving average PM concentrations from days 0-7 before suicide.

RESULTS

We confirmed an association between exposure to PM10 (≤ 10 μm in diameter) and deaths due to suicide. In particular, among individuals with psychiatric disorders and those who employed non-violent suicide methods, increased exposure to PM10 was associated with a higher risk of death by suicide, with percentage changes of 5.92 (95% confidence interval [CI]: 3.95-7.92) and 11.47 (95% CI: 7.95-15.11), respectively. Furthermore, in the group with psychiatric disorders, there was an observed tendency of increasing suicide risk as PM10 levels increased up to 120 µg/m3, whereas in the group with non-violent suicide deaths, there was a pronounced trend of rapid increase in suicide risk with an increase in PM10 up to 100 µg/m3.

CONCLUSIONS

These results show an association between short-term exposure to PM and suicide. Our study adds evidence for the benefits of reducing PM in preventing diseases and improving mental health.

Particulate matters (PM2.5, PM10) and the risk of depression among middle-aged and older population: analysis of the Korean Longitudinal Study of Aging (KLoSA), 2016-2020 in South Korea

BACKGROUND

There is a growing concern that particulate matter (PM) such as PM2.5 and PM10 has contributed to exacerbating psychological disorders, particularly depression. However, little is known about the roles of these air pollutants on depression in elderly. Therefore, this study aimed to examine the association between PM2.5 and PM10, and depression in the elderly population in South Korea.

METHODS

We used panel survey data, the Korean Longitudinal Study of Aging (KLoSA), administered by the Labor Institute during the study period of 2016, 2018, and 2020 covering 217 districts in South Korea (n = 7674). Annual district-specific PM2.5 and PM10 concentrations were calculated for the study period from the monthly prediction concentrations produced by a machine-learning-based ensemble model (cross-validated R2: 0.87), then linked to the people matching with year and their residential district. We constructed a generalized estimating equation (GEE) model with a logit link to identify the associations between each of the long-term PM2.5 and PM10 exposures and depression (CES-D 10) after adjusting for individual and regional factors as confounders.

RESULTS

In single-pollutant models, we found that long-term 10 [Formula: see text] increments in PM2.5 (OR 1.36, 95% CI 1.20-1.56) and PM10 (OR 1.19, 95% CI 1.10-1.29) were associated with an increased risk of depression in the elderly. Associations were consistent after adjusting for other air pollutants (NO2 and O3) in two-pollutant models. In addition, the impacts substantially differed by regions grouped by the tertile of the population density, for which the risks of particulate matters on depression were substantial in the middle- or high-population-density areas in contrast to the low-population-density areas.

CONCLUSIONS

Long-term exposure to PM2.5 and PM10 was associated with a higher risk of developing depression in elderly people. The impact was modified by the population density level of the region where they reside.

Daylight during winters and symptoms of depression and sleep problems: A within-individual analysis

BACKGROUND

With climate change Northern areas of the globe are expected to have less daylight during winters due to less snow and more cloudiness. While wintertime has been linked to mental health problems, the role of wintertime daylight has been scarcely studied. We examined longitudinal associations for wintertime objective exposure to global radiation and self-reported daylight exposure with symptoms of depression and sleep problems.

METHODS

Our analytical sample included 15,619 respondents from three Swedish Longitudinal Occupational Surveys of Health (2012, 2014 and 2016). Objective exposure was global radiation (MJ/m2, November-January and November-February). Subjective exposure was based on self-reported time spent outdoors in daylight (<1 h vs. ≥ 1 h, November-January). Symptoms of depression were evaluated using a six-item subscale of the (Hopkins) Symptom Checklist. Fixed-effects method with conditional logistic regression controlled for time-invariant participant characteristics by design and time-varying covariates were added into models.

RESULTS

One unit increase in the four-month averaged global radiation was associated with lower odds of depressive symptoms (OR 0.69, 95 % CI 0.52-0.91). These findings were confirmed using four-month cumulative exposure (OR 0.91, 95 % CI 0.85-0.98). Individuals reporting ≥ 1 h exposure to daylight during winter months were less likely to report depressive symptoms (OR 0.72, 95 % CI 0.60-0.82) compared to time when their exposure was < 1 h. Higher three-month exposure to global radiation suggested a protective association for sleep problems.

CONCLUSION

These findings suggest that higher exposure to daylight during winters may contribute to lower likelihood of depression symptoms.

Association between prenatal period exposure to ambient air pollutants and development of postpartum depression: a systematic review and meta-analysis

There is body of evidence supporting a role for maternal exposure to ambient air pollutants and postpartum depression (PPD). We attempted to review the literature systematically to assess the association between exposure to both ambient air particulate matters within pregnancy and PPD. The effect estimates extracting across each study were standardized to a 10 μg/m3 change. The random-effects model was applied to pool odds ratios. According to the three included cohort articles, exposure to PM10 within second trimester (OR = 1.26, 95% CI = 1.15-1.37) was significantly associated with higher odds of PPD. However, there was no significant association between having exposure to other ambient air pollutants and PPD. This meta-analysis showed that air pollutants could be associated with an increased risk of PPD.

Meteorological factors, ambient air pollution, and daily hospital admissions for depressive disorder in Harbin: A time-series study

BACKGROUND

The literature has discussed the relationship between environmental factors and depressive disorders; however, the results are inconsistent in different studies and regions, as are the interaction effects between environmental factors. We hypothesized that meteorological factors and ambient air pollution individually affect and interact to affect depressive disorder morbidity.

AIM

To investigate the effects of meteorological factors and air pollution on depressive disorders, including their lagged effects and interactions.

METHODS

The samples were obtained from a class 3 hospital in Harbin, China. Daily hospital admission data for depressive disorders from January 1, 2015 to December 31, 2022 were obtained. Meteorological and air pollution data were also collected during the same period. Generalized additive models with quasi-Poisson regression were used for time-series modeling to measure the non-linear and delayed effects of environmental factors. We further incorporated each pair of environmental factors into a bivariate response surface model to examine the interaction effects on hospital admissions for depressive disorders.

RESULTS

Data for 2922 d were included in the study, with no missing values. The total number of depressive admissions was 83905. Medium to high correlations existed between environmental factors. Air temperature (AT) and wind speed (WS) significantly affected the number of admissions for depression. An extremely low temperature (-29.0 ℃) at lag 0 caused a 53% [relative risk (RR)= 1.53, 95% confidence interval (CI): 1.23-1.89] increase in daily hospital admissions relative to the median temperature. Extremely low WSs (0.4 m/s) at lag 7 increased the number of admissions by 58% (RR = 1.58, 95%CI: 1.07-2.31). In contrast, atmospheric pressure and relative humidity had smaller effects. Among the six air pollutants considered in the time-series model, nitrogen dioxide (NO2) was the only pollutant that showed significant effects over non-cumulative, cumulative, immediate, and lagged conditions. The cumulative effect of NO2 at lag 7 was 0.47% (RR = 1.0047, 95%CI: 1.0024-1.0071). Interaction effects were found between AT and the five air pollutants, atmospheric temperature and the four air pollutants, WS and sulfur dioxide.

CONCLUSION

Meteorological factors and the air pollutant NO2 affect daily hospital admissions for depressive disorders, and interactions exist between meteorological factors and ambient air pollution.

Association Between Sunlight Exposure and Mental Health: Evidence from a Special Population Without Sunlight in Work

Purpose

In recent years, mental health problems have become the most serious social problems worldwide. Past studies have proposed that some links exist between sunlight and mental health; however, relevant studies examining low-dose sunlight exposure populations are lacking. We conducted a study among a group of operating room nurses (ORNs) who work long hours in operating rooms and have limited sunlight exposure. We aim to add to and refine previous researches on the association between mental health and sunlight exposure in community population.

Patients and Methods

A total of 787 ORNs were interviewed and analyzed. Mental health, sunlight exposure duration, sociodemographic and work-related variables, and chronic diseases were evaluated. The Kessler 10 scale (K10) was used to assess participants' mental health status, and their sunlight exposure duration was assessed using their self-reports. Multiple linear regression analysis was adopted to examine the association between sunlight exposure and mental health.

Results

The average K10 score of ORNs was 25.41. ORNs exhibit poorer mental health than other populations. Poor mental health was negatively associated with greater sunlight exposure hours per day (β=-0.378) and sleep regularity (β=-3.341). Poor mental health was positively associated with chronic disease (β=3.514).

Conclusion

This study indicated that the positive association between sunlight exposure and mental health existed. Appropriate enhancement of sunlight exposure will be beneficial to mental health. Hospitals, related organizations and individuals should pay greater attention to ORNs' mental health and sunlight exposure conditions. More policy recommendations as well as building structure recommendations should be proposed.

Computational Study of Photodegradation Process and Conversion Products of the Antidepressant Citalopram in Water

Citalopram (CIT) is a commonly prescribed medication for depression. However, the photodegradation mechanism of CIT has not yet been fully analyzed. Therefore, the photodegradation process of CIT in water is studied by density functional theory and time-dependent density functional theory. The calculated results show that during the indirect photodegradation process, the indirect photodegradation of CIT with ·OH occurs via OH-addition and F-substitution. The minimum activation energy of C10 site was 0.4 kcal/mol. All OH-addition and F-substitution reactions are exothermic. The reaction of ¹O₂ with CIT includes the substitution of ¹O₂ for F and an addition reaction at the C14 site. The E_a value of this process is 1.7 kcal/mol, which is the lowest activation energy required for the reaction of ¹O₂ with CIT. C-C/C-N/C-F cleavage is involved in the direct photodegradation process. In the direct photodegradation of CIT, the activation energy of the C7-C16 cleavage reaction was the lowest, which was 12.5 kcal/mol. Analysis of the E_a values found that OH-addition and F-substitution, the substitution of ¹O₂ for F and addition at the C14 site, as well as the cleavage reactions of C6-F/C7-C16/C17-C18/C18-N/C19-N/C20-N are the main pathways of photodegradation of CIT.

Association of time spent in outdoor light and genetic risk with the incidence of depression

Depression is the consequence of both environment and genes working together. Genetic factors increase depression risk, but it is unclear whether this association can be offset by time spent in outdoor light. The study was undertaken to investigate the optimal time spent in outdoor light for lowering the risk of depression and the joint association of time spent in outdoor light and depression genetic risk. In UK Biobank, 380,976 depression-free individuals were included in this study. Polygenic risk score (PRS) was categorized into three groups in terms of tertiles. Time spent in outdoor light on a typical day in summer or winter originated from the questionnaire survey. Depression was defined as hospital admission. The potential dose-response relationship between time spent in outdoor light and depression risk was shown by a restricted cubic spline. Data were analyzed using Cox regressions and Laplace regression. After the median follow-up of 12.6 years, 13,636 individuals suffered from depression in the end. A nonlinear (J-shaped relationship) trend was observed between time spent in outdoor light and depression risk. On average, 1.5 h/day of outdoor light was related to the minimum risk of depression. Individuals below and above this optimal time both had elevated depression risk (below, HR = 1.09, 95% CI: 1.02-1.16; above, HR = 1.13, 95% CI: 1.07-1.20), and the time to incident depression were both shortened by 0.46 years (50th percentile differences [PD] = -0.46, 95% CI: -0.78, -0.14) and 0.63 years (50th PD = -0.63, 95% CI: -0.90, -0.35) years, respectively. In a comparison of individuals with the lowest tertile of PRS and average 1.5 h/day outdoor light, the HRs and 95% CIs of depression were 1.36 (1.21-1.53) and 1.43 (1.29-1.58) in those with the highest tertile of PRS and below/above this reference value, respectively. Significant multiplicative interactions were observed between intermediate genetic risks and longer time spent in outdoor light. We found that an average of 1.5 h/day spent in outdoor light was associated with a lower depression risk whatever the degree of depression genetic predisposition. Moderate time spent in outdoor light may contribute to a decreased depression risk even among people with a higher genetic risk of depression.

The Short- and Long-Run Impacts of Air Pollution on Human Health: New Evidence from China

Under the background of the far-reaching impact of the COVID-19 epidemic on global economic development, the interactive effect of economic recovery and pollution rebound makes the research topic of air pollution and human health receive attention again. Matching a series of new datasets and employing thermal inversion as an instrumental variable, this study investigates the physical and mental health effect of air pollution jointly in China. We find that in the short run, the above inference holds for both physical and mental health. These short-run influences are credible after a series of robustness checks and vary with different individual characteristics and geographical locations. We also find that in the long run, air pollution only damages mental health. Finally, this study calculates the health cost of air pollution. The above findings indicate that in China, the effect of air pollution on physical and mental health cannot be ignored. The government needs to consider the heterogeneity and long-run and short-run differences in the health effects of air pollution when formulating corresponding environmental and medical policies.

The Psychosocial Impact of Chronic Facial Dermatoses in Adults

INTRODUCTION

Skin diseases have negative psychological and social consequences, especially when they are chronic and affect a visible area of the body, such as the face.

OBJECTIVES

The purpose of this study is to investigate and compare the psychosocial impact of three common chronic dermatoses of the face: acne, rosacea, and seborrheic dermatitis.

METHODS

The Dermatology Life Quality Index (DLQI), Hospital Anxiety and Depression Scale (HADS), and Social Appearance Anxiety Scale (SAAS) were used to compare acne, rosacea, and seborrheic dermatitis patients and healthy controls. The relationships between DLQI, HADS, and SAAS results were investigated, as well as their associations with disease duration and severity.

RESULTS

The study included 166 acne patients, 134 rosacea patients, 120 seborrheic dermatitis patients, and 124 controls. The patient groups had significantly higher DLQI, HADS, and SAAS scores than the control group. Rosacea patients had the highest DLQI and SAAS scores, as well as the highest anxiety prevalence. Patients with seborrheic dermatitis had the highest rate of depression. The DLQI, HADS, and SAAS results were moderately correlated with each other, but their relationship with disease duration and severity was insignificant or weak at best.

CONCLUSIONS

Chronic facial dermatoses have a detrimental impact on mood and quality of life. Although patients with acne, rosacea, and seborrheic dermatitis have distinct lesions, the outcomes in terms of quality of life, anxiety, and depression are largely similar. Furthermore, these patients report similar levels of social anxiety as a result of their overall appearance.

Effects of sunshine duration on daily outpatient visits for depression in Suzhou, Anhui Province, China

Previous epidemiological studies have reported seasonal variation patterns of depression symptoms, which may be influenced by bad weather conditions, such as a lack of sunlight. However, evidence on the acute effects of sunshine duration on outpatient visits for depression is limited, especially in developing countries, and the results are inconsistent. We collected daily outpatient visits for depression from the local mental health centre in Suzhou, Anhui Province, China, during 2017-2019. We defined the 5th and 95th sunshine percentiles as short and long sunshine durations, respectively. A quasi-Poisson generalized linear regression model combined with a distributed lag nonlinear model was used to quantitatively assess the effects of short and long sunshine durations on outpatient visits for depression. Stratified analyses were further performed by gender, age and number of visits to identify vulnerable populations. A total of 26,343 depression cases were collected during the study period. An approximate U-shaped exposure-response association was observed between sunshine duration and depression outpatient visits. The cumulative estimated relative risks (RRs) for short and long sunshine durations at lag 0-21 days were 1.53 [95% confidence intervals (CI): 1.14, 2.06] and 1.13 (95% CI: 0.88, 1.44), respectively. Moreover, a short sunshine duration was associated with a greater disease burden than a long sunshine duration, with attributable fractions (AFs) of 16.64% (95% CI: 7.8%, 23.89%) and 2.24% (95% CI: -2.65%, 5.74%), respectively. Subgroup analysis showed that males, people aged less than 45 years and first-visit cases may be more susceptible to a lack of sunlight. For a long sunshine duration, no statistically significant associations were found in any population groups. Our study found that a short sunshine duration was associated with an increased risk of depression. The government, medical institutions, family members and patients themselves should fully recognize the important role of sunlight and take active measures to prevent depression.

The Association between Self-Rated Health Status, Psychosocial Stress, Eating Behaviors, and Food Intake According to the Level of Sunlight Exposure in Korean Adults

Sunlight exposure has been reported to have various beneficial effects on human health. This study investigated the relationship between self-rated health status, psychosocial stress, eating behaviors, and food intake according to sunlight exposure in 948 adults. Sunlight exposure was classified as less than one hour, less than three hours, and greater than three hours. Of the participants, 49.2% had fewer than three hours of daily exposure to sunlight. Regarding participants exposed to sunlight for less than one hour, the largest response was that they did not engage in outdoor activities on weekdays or weekends, and the rate of being outdoors in the shade on sunny days was the highest in this group at 42.7%. Furthermore, the participants exposed to sunlight for less than one hour had a lower health response than the other two groups, and there were significantly more participants classified in the stress risk group. Regarding eating habits, those with less than an hour of exposure to sunlight frequently ate fried foods, fatty foods, added salt, and snacks, and had significantly lower total dietary scores or three regular meals. Additionally, their frequency of consumption of cereals, milk and dairy products, orange juice, and pork was also significantly lower than the other groups. Thus, it is necessary to provide sufficient guidelines for adequate sunlight exposure and food intake because participants with low sunlight exposure may have low vitamin D synthesis and insufficient food intake.

Long-term residential sunlight exposure associated with cognitive function among adults residing in Finland

While sunlight may influence cognitive function through several pathways, associations of residential sunlight exposure with cognitive function are not well known. We evaluated associations of long-term residential sunlight exposure with cognitive function among a representative cohort of 1838 Finnish adults residing in Finland who underwent comprehensive cognitive assessment in midlife. We linked daily recordings of global solar radiation to study participants using residential information and calculated the average daily residential exposure to sunlight for four exposure time intervals: 2 months, 1 year, 2 years and 5 years prior to the date of the cognition assessment. Associations of the residential sunlight exposure with cognitive function were assessed using linear regression analyses adjusting for season, sex, age, and individual- and neighborhood-level socioeconomic characteristics. Greater average residential sunlight exposure over 2 and 5 years prior to the cognitive function assessment was associated with better global cognitive function (b = 0.13, 95% CI = 0.01, 0.25; b = 0.17, 95% CI = 0.05, 0.29, per 1 MJ/m² difference in sunlight exposure), while no associations with global cognitive function were observed at shorter exposure time intervals. In domain-specific analyses, greater residential exposure to sunlight over 1, 2 and 5 years prior to the cognitive function assessment was associated with better performance on new learning and visual memory (b = 0.10, 95% CI = 0.00, 0.20; b = 0.16, 95% CI = 0.04, 0.28; b = 0.19, 95% CI = 0.08, 0.31) and sustained attention (b = 0.15, 95% CI = 0.05, 0.25; b = 0.18, 95% CI = 0.06, 0.30; b = 0.17, 95% CI = 0.05, 0.29), but worse performance on reaction time (b =  - 0.12, 95% CI =  - 0.22, - 0.02; b = -0.15, 95% CI =  - 0.28, - 0.02; b =  - 0.18, 95% CI =  - 0.30, - 0.05). Residential sunlight exposure was not associated with executive function. These findings suggest long-term residential sunlight exposure may be an environmental factor influencing cognitive function among a cognitively healthy cohort residing in Northern Europe. Further studies in populations residing in different geographical locations are needed.

Long-term exposure to air pollution and mortality from dementia, psychiatric disorders, and suicide in a large pooled European cohort: ELAPSE study

Ambient air pollution is an established risk factor for premature mortality from chronic cardiovascular, respiratory and metabolic diseases, while evidence on neurodegenerative diseases and psychiatric disorders remains limited. We examined the association between long-term exposure to air pollution and mortality from dementia, psychiatric disorders, and suicide in seven European cohorts. Within the multicenter project 'Effects of Low-Level Air Pollution: A Study in Europe' (ELAPSE), we pooled data from seven European cohorts from six countries. Based on the residential addresses, annual mean levels of fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), black carbon (BC), ozone (O₃), and 8 PM_2.5 components were estimated using Europe-wide hybrid land-use regression models. We applied stratified Cox proportional hazard models to investigate the associations between air pollution and mortality from dementia, psychiatric disorders, and suicide. Of 271,720 participants, 900 died from dementia, 241 from psychiatric disorders, and 164 from suicide, during a mean follow-up of 19.7 years. In fully adjusted models, we observed positive associations of NO₂ (hazard ratio [HR] = 1.38; 95 % confidence interval [CI]: 1.13, 1.70 per 10 µg/m³), PM_2.5 (HR = 1.29; 95 % CI: 0.98, 1.71 per 5 µg/m³), and BC (HR = 1.37; 95 % CI: 1.11, 1.69 per 0.5 × 10^-5/m) with psychiatric disorders mortality, as well as with suicide (NO₂: HR = 1.13 [95 % CI: 0.92, 1.38]; PM_2.5: HR = 1.19 [95 % CI: 0.76, 1.87]; BC: HR = 1.08 [95 % CI: 0.87, 1.35]), and no association with dementia mortality. We did not detect any positive associations of O₃ and 8 PM_2.5 components with any of the three mortality outcomes. Long-term exposure to NO₂, PM_2.5, and BC may lead to premature mortality from psychiatric disorders and suicide.

Short-Term Exposure to Ambient Air Pollution and Hospital Admissions for Sequelae of Stroke in Chinese Older Adults

Extensive evidence suggests that ambient air pollution contributes to a higher risk of hospital admissions for cerebrovascular diseases; however, its association with admissions for sequelae of stroke remains unclear. A time-stratified case-crossover study was conducted among 31,810 older adults who were admitted to hospital for sequelae of stroke in Guangzhou, China during 2016-2019. For each subject, daily residential exposure to fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ozone (O₃) was extracted from a validated grid data set. Conditional logistic regression models were used for exposure-response analyses. In single-pollutant models, each interquartile range (IQR) increase of lag 04-day exposure to CO (IQR: 0.25 mg/m³) and lag 3-day exposure to O₃ (69.6 μg/m³) was significantly associated with a 4.53% (95% confidence interval: 1.67%, 7.47%) and 5.63% (1.92%, 9.48%) increase in odds of hospital admissions for sequelae of stroke, respectively. These associations did not significantly vary across age or sex. With further adjustment for each of the other pollutants in 2-pollutant models, the association for CO did not change significantly, while the association for O₃ disappeared. We estimated that 7.72% of the hospital admissions were attributable to CO exposures. No significant or consistent association was observed for exposure to PM_2.5, PM₁₀, SO₂, or NO₂. In conclusion, short-term exposure to ambient CO, even at levels below the WHO air quality guideline, was significantly associated with an increased odds of hospital admissions for sequelae of stroke, which may lead to considerable excess hospital admissions.

Saving light, losing lives: How daylight saving time impacts deaths from suicide and substance abuse

This paper estimates the impact of Daylight Saving Time (DST) on deaths from suicide and substance abuse in the United States. Using Multiple Cause-of-Death Mortality Data from the National Vital Statistics System of the National Center for Health Statistics from 1979 to 1988, the effect is identified in two ways: a regression discontinuity design that exploits discrete time changes in the Spring and Fall; and a fixed effects model that uses a policy change and a switching mechanism that introduces random variation to DST's start and end dates. This is one of the first attempts to estimate the impact of DST on deaths due to suicide and substance abuse and the first to use either identification strategy. The results from both methods suggest that the sleep disruptions during the Spring transition cause the suicide rate to rise by 6.25 percent and the death rate from suicide and substance abuse combined to increase by 6.59 percent directly after the time change. There is no evidence for any change in these outcomes during the Fall transition. The contrasting results from Spring to Fall suggest the entire effect can be attributed to disruptions in sleep patterns rather than changes in ambient light exposure.

Artificial light at night and risk of mental disorders: A systematic review

BACKGROUND

Emerging evidence suggests a possible association between artificial light at night (LAN) exposure and physiological and behavioral changes, with implications on mood and mental health. Due to the increased amount of individuals' LAN exposure, concerns have been raised regarding harmful impact of light pollution on mental health at the population level.

AIM

To perform a systematic review of observational studies to investigate if light at night, assessed both indoor and outdoor, may be associated with an increased risk of mental diseases in humans.

METHODS

We reviewed the epidemiological evidence on the association between LAN exposure, assessed either via satellite photometry or via measurements of bedroom brightness, and mental disorders. We systematically searched the PubMed, Embase and Web of Science databases up to April 1, 2022. Studies were included if they assessed the link between indoor or outdoor artificial light at night and one or more mental disorders in human populations.

RESULTS

Nine eligible studies were included in this review: six studies had a cross-sectional design, two had a longitudinal design with a median follow-up of 24 months, and one was a case-cohort study. Overall, we found moderate evidence of a positive association between LAN exposure and depressive symptoms and to a lesser extent other mental disorders, though the number of studies was limited and potential residual confounding such as socioeconomic factors, noise, or air pollution may have influenced the results.

CONCLUSIONS

Although more robust evidence is needed, the epidemiological evidence produced so far seems to support an association between LAN and risk of depressive disorders.

Recent Techniques in Determining the Effects of Climate Change on Depressive Patients: A Systematic Review

Climate change is amongst the most serious issues nowadays. Climate change has become a concern for the scientific community as it could affect human health. Researchers have found that climate change potentially impacts human mental health, especially among depressive patients. However, the relationship is still unclear and needs further investigation. The purpose of this systematic review is to systematically evaluate the evidence of the association between climate change effects on depressive patients, investigate the effects of environmental exposure related to climate change on mental health outcomes for depressive patients, analyze the current technique used to determine the relationship, and provide the guidance for future research. Articles were identified by searching specified keywords in six electronic databases (Google Scholar, PubMed, Scopus, Springer, ScienceDirect, and IEEE Digital Library) from 2012 until 2021. Initially, 1823 articles were assessed based on inclusion criteria. After being analyzed, only 15 studies fit the eligibility criteria. The result from included studies showed that there appears to be strong evidence of the association of environmental exposure related to climate change in depressive patients. Temperature and air pollution are consistently associated with increased hospital admission of depressive patients; age and gender became the most frequently considered vulnerability factors. However, the current evidence is limited, and the output finding between each study is still varied and does not achieve a reasonable and mature conclusion regarding the relationship between the variables. Therefore, more evidence is needed in this domain study. Some variables might have complex patterns, and hard to identify the relationship. Thus, technique used to analyze the relationship should be strengthened to identify the relevant relationship.

Associations of long-term solar insolation with specific depressive symptoms: Evidence from a prospective cohort study

Evidence suggests that sunlight counteracts depression, but the associations of long-term sunlight exposure with specific symptoms of depression are not well known. We evaluated symptom-specific associations of average 1-year solar insolation with DSM-5 depressive symptoms in a representative cohort of Finnish adults. The sample included 1,845 participants from the Cardiovascular Risk in Young Finns Study with data on DSM-5 depressive symptoms, place of residence and covariates. Daily recordings of global solar radiation were obtained from the Finnish Meteorological Institute. Each participant's residential zip code on each day one year prior to the assessment of depressive symptoms was linked to the solar radiation data, and 1-year average daily solar insolation was calculated. Associations of the average 1-year solar insolation with depressive symptoms were assessed with linear and logistic regression analyses adjusting for season, sex, age, as well as individual- and neighborhood-level socioeconomic characteristics. Average daily solar insolation over one year prior to the depressive symptom assessment was not associated with the total number of depressive symptoms reported by participants. In symptom-specific analyses, participants exposed to higher levels of solar insolation in their residential neighborhood were less likely to report suicidal thought (OR = 0.61, 95% CI, 0.39-0.94), and more likely to report changes in appetite (OR = 1.24, 95% CI, 1.00-1.54), changes in sleep (OR = 1.30, 95% CI, 1.06-1.59) and feelings of worthlessness/guilt (OR = 1.33, 95% CI = 1.07-1.65). These findings suggest that solar insolation may contribute to symptom-specific differences in depression. Studies in other populations residing in different geographical locations are needed.

An Evaluation of Risk Ratios on Physical and Mental Health Correlations due to Increases in Ambient Nitrogen Oxide (NOx) Concentrations

Nitrogen oxides (NOx) are gaseous pollutants contributing to pollution in their primary form and are also involved in reactions forming ground-level ozone and fine particulate matter. Thus, NOx is of great interest for targeted pollution reduction because of this cascade effect. Primary emissions originate from fossil fuel combustion making NOx a common outdoor and indoor air pollutant. Numerous studies documenting the observed physical health impacts of NOx were reviewed and, where available, were summarized using risk ratios. More recently, the literature has shifted to focus on the mental health implications of NOx exposure, and a review of the current literature found five main categories of mental health-related conditions with respect to NOx exposure: common mental health disorders, sleep, anxiety, depression, and suicide. All the physical and mental health effects with available risk ratios were organized in order of increasing risk. Mental health concerns emerged as those most influenced by NOx exposure, with physical health impacts, such as asthma, only beginning to surface as the fourth highest risk. Mental health conditions occupied seven of the top ten highest risk health ailments. The results summarized in this narrative review show that there are clear positive correlations between NOx and negative physical and mental health manifestations, thus strengthening the argument in support of the reduction in ambient NOx levels.

Short-Term exposure to ambient air pollution and onset of work incapacity related to mental health conditions

The OECD estimates that greater work absenteeism is one of the main drivers behind the impact of air pollution on gross domestic product loss, but research linking air pollution with work absenteeism is scarce. With air pollution increasingly being linked to poor mental health, and poor mental health having become one of the main reasons for work absenteeism, we examined whether the onset of work incapacity related to mental health conditions is associated with short-term fluctuations in ambient black carbon (BC), nitrogen dioxide (NO₂), ozone (O₃), and particulate matter 2.5 (PM_2.5), estimating the contributions of these pollutants jointly, while accounting for relative humidity, total solar radiation and temperature. We conducted a bidirectional time-stratified case-crossover study with daily air pollution estimates by municipality linked with 12 270 events of work incapacity related to mental health conditions in 2019 in Belgium. We ran single- and multi-pollutant conditional logistic regression models for three different exposure windows (lag 0, 0-1 and 0-2), considering potential confounding by relative humidity and total solar radiation. We observed positive associations between work incapacity related to mental health conditions and BC, NO₂, and O₃ exposure, but findings for PM_2.5 were inconsistent. Results from multi-pollutant models showed a 12% higher risk of work incapacity for an IQR increase in NO₂ and O₃ at the day of the event (lag 0), with estimates increasing to about 26% for average concentrations up to two days before the event (lag 0-2). We found evidence for effect modification by age and season in the association with NO₂, with highest effect estimates in the age group 40-49 years and in spring and summer. For O₃, we observed effect modification by type of mental health problem. This country-wide study suggests that air pollution aggravates within 48 h a likely existing propensity to enter work incapacity because of mental health conditions.

Air Pollution, Foreign Direct Investment, and Mental Health: Evidence From China

Recently, there has been interest in the relationship between mental health and air pollution; however, the results are inconsistent and the contribution of foreign direct investment (FDI) has received little attention. This article studies the effects of air pollution on mental health and the moderating role of FDI based on the China Health and Retirement Longitudinal Study (CHARLS) data in 2015 and 2018 applying the fixed effects panel regression approach and the threshold model. The results show that mental health is adversely affected by air pollution, especially PM_2.5, PM₁₀, sulfur dioxide (SO₂), carbon monoxide (CO), and nitrogen dioxide (NO₂). Second, FDI has an alleviating influence on the negative relationship. Third, the effects of air pollution and FDI are heterogeneous based on regional characteristics, including location, medical resource and investment in science and technology, and individual characteristics covering education level, age, income, and physical health. Finally, the threshold effects show that FDI has a moderating effect when it is >1,745.59 million renminbi (RMB). There are only 11.19% of cities exceeding the threshold value in China. When the value of air quality index (AQI) exceeds 92.79, air pollution is more harmful to mental health. Government should actively introduce high-quality FDI at the effective level and control air pollution to improve mental health.

Attributable risk and economic cost of hospital admissions for depression due to short-exposure to ambient air pollution: A multi-city time-stratified case-crossover study

BACKGROUND

Depression has become the most common mental disease globally and is a strong predictor for suicide. Studies have indicated that exposure to high levels of air pollution increased the risk of depression, but evidence in human populations is still limited. At present, a few studies estimated the impact of multi-pollutants on hospitalization for depression in multi-city in areas with severe air pollution. We aimed to examine the association between short-term exposure to common ambient air pollutants and hospital admissions (HAs) for depression based on statistics of inpatients with depression in multi-city.

METHODS

The 10,459 records of HAs for depression from medical institutions in nine cities/prefectures, Sichuan Province, China, between January 1, 2017 and December 31, 2018 were collected. Air pollutant data including PM_2.5, PM₁₀, SO₂ and NO₂ from provincial ecological environment monitoring stations were obtained. Based on a time-stratified case-crossover design, we estimated the impact on relative risk (RR) of short-term exposure to air pollutants on hospitalization for depression, with stratification by sex, age, and economic level. The cost of illness method was used to further assess hospitalization costs.

RESULTS

The short-term exposure to air pollutants was positively associated with hospitalization for depression. The increase of air particulate matter (PM) had the strongest effect on lag 0 day (PM_2.5:1.037 (95% CI:1.022,1.052), PM₁₀:1.024 (95% CI:1.013,1.036)). The effects of SO₂ reached the peak on lag 2 day (1.317 (95% CI:1.151,1.507)). Women and older people were more likely to be affected by air pollutants and prone to depression (P = 0.013, P = 0.006). During the study period, the economic cost of hospitalization for depression caused by PM pollution was US$ 8.36 million.

LIMITATIONS

The air pollutant concentration level of the monitoring stations in the study area was regarded as personal pollutant exposure, which may not accurately reflect the patient's exposure level, resulting in a certain measurement error.

CONCLUSIONS

Short-term changes to ambient air pollution exposure may increase the risk of hospital admissions for depression and cause economic costs due to hospitalization.

Air pollution and mental health: associations, mechanisms and methods

PURPOSE OF REVIEW

There is increasing interest in the links between exposure to air pollution and a range of health outcomes. The association with mental health however is much less established. This article reviews developments in the field over the past 12 months, highlighting the evidence for causation, associations between multiple air pollutants and mental health outcomes, and assesses the challenges of researching this topic.

RECENT FINDINGS

Increasingly rigorous methods are being applied to the investigation of a broader range of mental health outcomes. These methods include basic science, neuroimaging, and observational studies representing diverse geographical locations. Cohort studies with linked high-resolution air pollutant exposure data are common, facilitating advanced analytic methods. To date, meta-analyses have demonstrated small and significant positive associations between long-term exposure to fine particulate matter and depressive symptoms and cognitive decline. Methodological complexities in measuring exposure and outcome pose ongoing difficulties for the field.

SUMMARY

Literature on this topic has recently seen an appreciable expansion. Work that better estimates daily exposure, controls for complex confounders, and is driven by hypotheses founded in candidate causal mechanisms would help clarify associations, and inform targeted interventions and policymakers.

Associations Between Symptoms of Depression and Air Pollutant Exposure Among Older Adults: Results From the Taiwan Longitudinal Study on Aging (TLSA)

Background: Little epidemiological research has investigated the associations of air pollutant exposure over various time windows with older adults' symptoms of depression. This study aimed to analyze the relationships of long- and short-term ambient air pollution exposure (to coarse particulate matter, O₃, SO₂, CO, and NO_x) with depressive symptoms in a sample of community-dwelling older adults.

Methods: A sample of older adults (n = 1,956) was recruited from a nationally representative multiple-wave study (Taiwan Longitudinal Study on Aging). Between 1996 and 2007, four waves of surveys investigated depressive symptoms by using the 10-item Center for Epidemiologic Studies Depression questionnaire. We approximated air pollutant concentrations from 1995 to 2007 by using daily concentration data for five air pollutants at air quality monitoring stations in the administrative zone of participants' residences. after adjusting for covariates, we applied generalized linear mixed models to analyze associations for different exposure windows (7-, 14-, 21-, 30-, 60-, 90-, and 180-day and 1-year moving averages).

Results: In a one-pollutant model, long- and short-term exposure to CO and NO_x was associated with heightened risks of depressive symptoms; the odds ratio and corresponding 95% confidence interval for each interquartile range (IQR) increment in CO at 7-, 14-, 21-, 30-, 60-, 90-, and 180-day and 1-year moving averages were 1.232 (1.116, 1.361), 1.237 (1.136, 1.348), 1.216 (1.128, 1.311), 1.231 (1.133, 1.338), 1.224 (1.124, 1.332), 1.192 (1.106, 1.285), 1.228 (1.122, 1.344), and 1.180 (1.102, 1.265), respectively. Those for each IQR increment in NO_x were 1.312 (1.158, 1.488), 1.274 (1.162, 1.398), 1.295 (1.178, 1.432), 1.310 (1.186, 1.447), 1.345 (1.209, 1.496), 1.348 (1.210, 1.501), 1.324 (1.192, 1.471), and 1.219 (1.130, 1.314), respectively. The exposure to PM₁₀, O₃, and SO₂ over various windows were not significant. In the two-pollutant model, only the associations of NO_x exposure with depressive symptoms remained robust after adjustment for any other pollutant.

Conclusions: Exposure to traffic-associated air pollutants could increase depression risks among older adults.

Time spent in outdoor light is associated with the risk of dementia: a prospective cohort study of 362094 participants

BACKGROUND

Data on the association between free-living daytime sunlight exposure and incident dementia are scarce. The objective is to evaluate whether the time spent in outdoor light is related to the dementia risk and to investigate whether the optimal duration varies with clinical parameters.

METHODS

Data were from a prospective cohort of 362,094 UK Biobank participants. A questionnaire survey was conducted to investigate how many hours the participants spent outdoors on typical summer and winter days. A restricted cubic spline (RCS) was performed to explore the potential nonlinear relationship between sunlight exposure and the risk of dementia. We used multivariate Cox proportional hazard regression models to estimate the hazard ratios (HRs) for the associations between sunlight exposure and dementia outcomes, with the change points as a reference.

RESULTS

After a median follow-up of 9.0 years, 4149 (1.15%) individuals were diagnosed with dementia. RCS showed a J-shaped relationship between time spent in outdoor light and the dementia risk, with the lowest risk at three change points (1.5 h/day on average, 2 h/day in summer, and 1 h/day in winter). Cox hazard regression models showed a marked increase in risk at low exposure (HR=1.287, 95%CI 1.094-1.515) but a relatively slow increase at higher exposure (HR=1.070, 95%CI 1.031-1.10). Results are more pronounced among participants over 60 years old, females, and those with exactly 7 h of sleep every night.

CONCLUSIONS

Sunlight exposure had a J-shaped association with dementia risk. Giving detailed guidance on sunlight exposure can effectively prevent dementia.

Influence of External Natural Environment Including Sunshine Exposure on Public Mental Health: A Systematic Review

The COVID-19 pandemic has been raging around the world and public health measures such as lockdowns have forced people to go out less often, reducing sunlight exposure time, green space use, and physical activity. It is well known that exercise has a positive impact on mental health, but the impact of external environmental factors such as sunlight exposure and green space use on mental health has not been systematically reviewed. In this review, we categorized the major factors that may affect people’s mental health into (1) external environmental factors such as exposure to sunlight and green spaces, (2) internal life factors such as physical activity and lifestyle, and (3) mixed external and internal factors, and systematically examined the relationship between each factor and people’s mental health. The results showed that exposure to sunlight, spending leisure time in green spaces, and physical activity each had a positive impact on people’s mental health, including depression, anxiety, and stress states. Specifically, moderate physical activity in an external environment with sunlight exposure or green space was found to be an important factor. The study found that exposure to the natural environment through sunbathing and exercise is important for people’s mental health.

Population Health Effects of Air Pollution: Fresh Evidence From China Health and Retirement Longitudinal Survey

The effects of air pollution on population health are currently a hot topic. However, few studies have examined the physical and mental health effects of air pollution jointly in China. Using data from the China Health and Retirement Longitudinal Study (CHARLS) in 2015 and 2018, this study explores how air pollution affects the physical and mental health of middle-aged and elderly residents. The empirical results highlight that air pollution can negatively affect both physical and mental health. In terms of physical health, those exposed to chronic shock are likely to suffer more adverse effects from air pollution than those exposed to acute shock. In terms of mental health, those exposed to depression suffer greater adverse effects than those exposed to episodic memory and mental cognition. Besides, heterogeneity analysis also shows that air pollution affects the mental and physical health of males more than females. Furthermore, the increase in air pollution is expected to result in huge hospitalization costs. Therefore, the Chinese government should formulate differentiated public health policies to reduce the effects of air pollution on the health of middle-aged and elderly residents.

The Brain-Skin Axis in Psoriasis-Psychological, Psychiatric, Hormonal, and Dermatological Aspects

Psoriasis is a chronic inflammatory skin disease with systemic manifestation, in which psychological factors play an important role. The etiology of psoriasis is complex and multifactorial, including genetic background and environmental factors such as emotional or physical stress. Psychological stress may also play a role in exacerbation of psoriasis, by dysregulation of the hypothalamic–pituitary–adrenal (HPA) axis, sympathetic–adrenal–medullary axis, peripheral nervous system, and immune system. Skin cells also express various neuropeptides and hormones in response to stress, including the fully functional analog of the HPA axis. The deterioration of psoriatic lesions is accompanied by increased production of inflammatory mediators, which could contribute to the imbalance of neurotransmitters and the development of symptoms of depression and anxiety. Therefore, deregulation of the crosstalk between endocrine, paracrine, and autocrine stress signaling pathways contributes to clinical manifestations of psoriasis, which requires multidisciplinary approaches.

Photodegradation of three antidepressants in natural waters: Important roles of dissolved organic matter and nitrate

Antidepressants have become ubiquitous emerging organic pollutants. Therefore, it is essential to investigate photodegradation of the antidepressants in environment waters for their ecological risk assessment. However, photodegradation behavior of antidepressants varied from different structures and photodegradation mechanism was rarely known for most antidepressants. Herein, citalopram (CIT), paroxetine (PAR) and fluvoxamine (FLUVO) were employed to study the photodegradation behavior of antidepressants in lake water. Results show that direct photolysis of CIT decreased when pH increased from 6 to 9 while the pH effect was not obvious on direct photolysis of FLUVO and PAR. Photodegradation of CIT occurred from its triplet-state and can undergo self-photosensitization through reaction with the generated hydroxyl radical (·OH). In lake water, PAR and FLUVO are degraded mainly via direct photolysis, while CIT is transformed mainly via indirect photolysis. Dissolved organic matter (DOM) and NO₃^- was proved to be the main factors affecting antidepressants photodegradation in lake water. DOM and NO₃^- showed inhibition effect on photodegradation of FLUVO and PAR, while promoted CIT degradation. The promotion effect of CIT was mainly through reaction with ·OH and excited triplet-state of DOM while singlet oxygen played a minor role. Based on the photodegradation products identified by MS/MS, the photodegradation pathways were proposed for CIT and PAR, respectively. For FLUVO, one (Z)-isomer degradation product was also found. Understanding the photodegradation behavior of antidepressants is vital for providing data to do ecological risk assessment.

Air pollution exposure and depression: A comprehensive updated systematic review and meta-analysis

We provide a comprehensive and updated systematic review and meta-analysis of the association between air pollution exposure and depression, searching PubMed, Embase, and Web of Sciences for relevant articles published up to May 2021, and eventually including 39 studies. Meta-analyses were performed separately according to pollutant type [particulate matter with diameter ≤10 μm (PM₁₀) and ≤2.5 μm (PM_2.5), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), and carbon monoxide (CO)] and exposure duration [short- (<30 days) and long-term (≥30 days)]. Test for homogeneity based on Cochran's Q and I² statistics were calculated and the restricted maximum likelihood (REML) random effect model was applied. We assessed overall quality of pooled estimates, influence of single studies on the meta-analytic estimates, sources of between-study heterogeneity, and publication bias. We observed an increased risk of depression associated with long-term exposure to PM_2.5 (relative risk: 1.074, 95% confidence interval: 1.021-1.129) and NO₂ (1.037, 1.011-1.064), and with short-term exposure to PM₁₀ (1.009, 1.006-1.012), PM_2.5 (1.009, 1.007-1.011), NO₂ (1.022, 1.012-1.033), SO₂ (1.024, 1.010-1.037), O₃ (1.011, 0.997-1.026), and CO (1.062, 1.020-1.105). The publication bias affecting half of the investigated associations and the high heterogeneity characterizing most of the meta-analytic estimates partly prevent to draw very firm conclusions. On the other hand, the coherence of all the estimates after excluding single studies in the sensitivity analysis supports the soundness of our results. This especially applies to the association between PM_2.5 and depression, strengthened by the absence of heterogeneity and of relevant publication bias in both long- and short-term exposure studies. Should further investigations be designed, they should involve large sample sizes, well-defined diagnostic criteria for depression, and thorough control of potential confounding factors. Finally, studies dedicated to the comprehension of the mechanisms underlying the association between air pollution and depression remain necessary.

A Data-Driven Analysis of Sociocultural, Ecological, and Economic Correlates of Depression Across Nations

The prevalence of depression varies widely across nations, but we do not yet understand what underlies this variation. Here we use estimates from the Global Burden of Disease study to analyze the correlates of depression across 195 countries and territories. We begin by identifying potential cross-correlates of depression using past clinical and cultural psychology literature. We then take a data-driven approach to modeling which factors correlate with depression in zero-order analyses, and in a multiple regression model that controls for covariation between factors. Our findings reveal several potential correlates of depression, including cultural individualism, daylight hours, divorce rate, and GDP per capita. Cultural individualism is the only factor that remains significant across all our models, even when adjusting for spatial autocorrelation, mental healthcare workers per capita, multicollinearity, and outliers. These findings shed light on how depression varies around the world, the sociocultural and environmental factors that underlie this variation, and potential future directions for the study of culture and mental illness.

Energy Consumption and Health Insurance Premiums in China's Provinces: Evidence From Asymmetric Panel Causality Test

This article employs asymmetric panel causality test to address the causal nexus between energy consumption (EC) and healthcare insurance premiums (IP) for China's different provinces. The empirical results indicate that there exist asymmetric causality runs from positive EC shocks to positive healthcare IPs in Beijing, Hebei, Tianjin, Shanxi, Inner Mongolia, Shaanxi, Gansu, Qinghai, Ningxia, Shandong, Henan, and Anhui. There is no significant link in southern and northeastern provinces mainly because of their industrial structure, high economic development level, strong insurance consciousness, and climate conditions. Therefore, governments should encourage technological innovation and further improve energy efficiency. Meanwhile, we need to optimize EC structure and raise the proportion of renewable energies. The authorities should carry out stricter environmental protection policies and protect people from pollution that comes from fossil fuel burn. The commercial health insurance should be included in the health system and become an important supplement to public health insurance.